The purpose of this study is to investigate the best fleet for a new purchase based on multi-objective optimization on the basis of ratio (MOORA), reference point and…
The purpose of this study is to investigate the best fleet for a new purchase based on multi-objective optimization on the basis of ratio (MOORA), reference point and multi-MOORA methods. This study further identifies critical parameters for fleet performance monitoring and exploring optimum range of critical parameters using Monte Carlo simulation. At the end of this study, fleet maintenance management and operations have been discussed in the perspectives of risk management.
Fleet categories and fleet performance monitoring parameters have been identified using the literature survey and Delphi method. Further, real-time data has been analyzed using MOORA, reference point and multi-MOORA methods. Taguchi and full factorial design of experiment (DOE) are used to investigate critical parameters for fleet performance monitoring.
Fleet performance monitoring is done based on fuel consumption (FC), CO2 emission (CE), coolant temperature (CT), fleet rating, revenue generation (RG), fleet utilization, total weight and ambient temperature. MOORA, reference point and multi-MOORA methods suggested the common best alternative for a particular category of the fleet (compact, hatchback and sedan). FC and RG are the critical parameters for monitoring the fleet performance.
The geographical aspects have not been considered for this study.
A pilot run of 300 fleets shows saving of Rs. 2,611,013/- (US$36,264.065), which comprises total maintenance cost [Rs. 1,749,033/- (US$24,292.125)] and FC cost [Rs. 861,980/- (US$11,971.94)] annually.
Reduction in CE (4.83%) creates a positive impact on human health. The reduction in the breakdown maintenance of fleet improves the reliability of fleet services.
This study investigates the most useful parameters for fleet management are FC, CE, CT. Taguchi DOE and full factorial DOE have identified FC and RG as a most critical parameters for fleet health/performance monitoring.
The purpose of this paper is to identify the risks involved in the construction project based on a literature survey (LS), to develop a project risk management (PRM…
The purpose of this paper is to identify the risks involved in the construction project based on a literature survey (LS), to develop a project risk management (PRM) framework based on Industry 4.0 technologies and to demonstrate the developed framework using Internet of Things (IoT) technology.
A comprehensive LS was carried out to know the different risks involved in the construction project and developed a PRM framework based on Industry 4.0 technologies to increase the effectiveness and efficiency of PRM. Heavy equipment and parameters were identified to demonstrate the developed framework based on IoT technology of Industry 4.0.
This paper demonstrates Industry 4.0 in the various stages of PRM. LS has identified 21 risks for a construction project. The demonstration of the PRM framework has identified the sudden breakdown of equipment and uncertainty of equipment as one of the critical risks associated with heavy equipment of construction project.
The project complexity and features may add a few more risks in PRM.
The PRM framework based on Industry 4.0 technologies will increase the success rate of the project. It will enhance the efficiency and effectiveness of PRM.
The developed framework is helpful for the effective PRM of construction projects. The demonstration of PRM framework using IoT technology provides a logical way to manage risk involved in heavy equipment used in a construction project.